Predictable variation and profitable trading of US equities: a trading simulation using neural networks

A switching rule conditioned on out-of-sample one-step-ahead predictions of returns is used to establish investment positions in either stocks or Trea sury bills, The economic significance of any discernible patterns of predic tability is assessed by incorporating transaction costs in the simulated tr ading strategies. We find that ANN models produce switching signals that co uld have been exploited by investors in an out-of-sample context to achieve superior cumulative and risk-adjusted returns when compared to either regr ession or a simple buy-and-hold strategy in the market indices, The robustn ess of these results across a large number of stock market indices is encou raging.